The RoboTuna is a robotic fish that will be able to collect samples from marine wildlife and allow us to better understand the oceanic ecosystem and the behavior of underwater creatures. This biomimetic robot will be able to get closer to fish and other creatures in their natural habitat than a person ordinarily could, and therefore will give new insights into how the underwater world is changing. Many of the RoboTuna’s pieces need to be flexible and waterproof, so casting and molding will be necessary to create them. The focus of this research was on fabricating a fin and air bladders for the RoboTuna, which included experimenting with different kinds of silicone rubber and urethane plastic. Existing soft robotic actuators have been extremely helpful to gain insight on how to move these parts without mechanical mechanisms. Shape memory alloys allow for simpler fin movement actuation instead of having to rely on a bulky motor. The same goes for moving the tail via air bladders, a kind of fluidic elastomer actuator. The differences between different kinds of silicones and how each material and molding method affected the fabricated parts are shown through flexibility and strength data. The information here can help future researchers determine what materials would be best for various parts of the RoboTuna and understand their options for soft robotic actuators.
A student project for AHSE1500: Foundations of Business and Entrepreneurship (taught in Spring 2006) featuring an Olin College themed tradable card game. It consists of cards of students, professors, locations, and events.
This record contains the Final Report for the project and scanned images of all the cards in the game.
The Rockwell Automation SCOPE team worked to provide an out-of-box quality control sensor for automation applications. Quality control sensors need to provide fast inspection capabilities for factories to ensure continuous quality of products. The team also looked into business opportunities for the sensor in line with Rockwell Automation’s industrial customer base. The team optimized the current sensor and made improvements. They also explored market segments where the sensor could make a significant impact on a factory’s quality control and automation processes.